Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already communicate read-only, idempotent, and non-destructive behavior. The description adds context about output content: results are ranked by relevance, include frequency and margin of leading, and are derived from chart co-occurrence. This goes beyond the structured annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences: a concise definition and a clarifying example question. Every sentence contributes value, with no fluff or restatement of the title.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the description doesn't need to explain return values. It covers the core concept, methodology, and a usage scenario. Some minor gaps remain (e.g., chart scope or prerequisite of user apps), but overall it is adequate given the annotations and schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description carries the full burden for explaining parameters. It mentions no parameter explicitly and does not clarify how end, limit, countries, platforms, or rangeDays affect results. The example question implies a high-level use case but fails to map any parameter to its meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly defines the tool's resource (rival apps) and action (discover via chart co-occurrence and outranking). It distinguishes itself from siblings like get_leaders or get_chart_top by focusing on apps that outrank the user's apps, reinforced by the example question.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Competitors discovered from the data rather than declared' implies when this tool is appropriate (data-driven discovery) versus a declared list. The example question provides a concrete usage scenario, but the description does not explicitly name alternative tools or formal exclusion conditions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.